Rungraungsilp, S., Boonlom, K., Robertson, I. et al. (2 more authors) (2025) Implement an acoustic sound system by Hann Window with Fast Fourier Transform (FFT) to analyze characteristics in a pipe for robotic. In: 2025 13th International Electrical Engineering Congress (iEECON). 2025 13th International Electrical Engineering Congress (iEECON), 05-07 Mar 2025, Hua Hin, Thailand. IEEE ISBN 979-8-3315-4396-9
Abstract
By measuring the amplitude utilizing the pipe's frequency range, we create an acoustic sound system to test in a pipe. In this study, we use digital signal processing techniques with a microphone to be a part of sensors. Our primary objective is to transmit signals from a loudspeaker or sender to the microphone or receiver while minimizing external noise and managing acoustic dispersion within the pipe. We develop an acoustic system based on pipes that can be applied to robotics in the future. Using a microphone and loudspeaker, we suggest the characteristics of the acoustic sound in the pipe. This subject is covered by the large field of acoustic signal processing. Our project intends to bring about a significant change in the management of buried pipe infrastructure in the future by developing specialized robots that can operate within subterranean pipe networks for communication. The assessment of acoustics in pipes using acoustic sound analysis is the focus of our research.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | microphone, acoustic measurements, pipelines, Hann Window, Fast Fourier Transform, sound absorption coefficient |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jul 2025 14:46 |
Last Modified: | 09 Jul 2025 14:46 |
Published Version: | https://ieeexplore.ieee.org/document/10987830 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ieecon64081.2025.10987830 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:228707 |